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Standard deviation percentiles determine the percentage of occurrences above or below the mean. In normal distributions, 50% of occurrences are less than or greater than the mean. Graphical displays are used to determine the importance of a score, and scores can be grouped into spreads based on the mean.
Standard deviation percentiles are used to determine the percentage of occurrences above or below a mean. In statistical analysis, the average of all numerical scores or occurrences is known as the mean. Because not all of the data you collect will be equal to the mean, the standard deviation reflects the distance from the mean of most of that data. In normal distributions, 50 percent of occurrences will be less than or greater than the mean of the dataset.
One of the most efficient ways to think of standard deviation percentiles is as the amount of occurrences that will be included in a range of numerical scores. For example, a group of college students in an economics class might get a series of final exam test scores. The mean will represent the mean score, and in most cases, a percentile of 50 percent will be assigned. Test scores that fall within one or two standard deviations of the mean will usually be assigned to a different percentile.
Standard deviation percentiles that fall below the mean in a normal distribution are less than 50%. Those that deviate higher or to the right of the mean will be more than 50 percent. For example, if the average exam score is 70, scores in the range of 71 to 81 could be assigned to the 75th percentile. Those scores ranging from 59 to 69, on the other hand, would most likely be within the 25th percentile.
Graphical displays of standard deviation percentiles are often used to determine the importance of a particular score. Individuals can use average salary statistics to see if a particular income is significantly higher or lower than the average. For example, a salary that matches the 90th percentile in a normal distribution means that the individual earns more than 90% of her peers. Standard deviation percentiles can also be grouped into spreads or ranges based on the mean of the dataset.
Using standard deviation percentiles, someone can easily determine if a numerical score is extremely high or low. In a class where a range of exam scores between 59 and 81 is within one standard deviation of the mean, 50% of students will most likely produce an exam score between 59 and 81. Scores below 59 or greater than 81 can be within two to three standard deviations of the mean.
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